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The cognitive processes of planning and scheduling are closely related to those discussed in the previous section, because informed problem solving and troubleshooting often involve careful planning of future tests and activities. However, troubleshooting and diagnosis generally suggest that something is “wrong” and needs to be fixed. Planning and scheduling do not have this implication. That is, planning may be invoked in the absence of problem solving, as when a routine schedule of activities is generated. Planning often accompanies decision making to implement the course of action decided upon. In many dynamic systems, the future may be broken down into two separate components: the predicted state of the system that is being controlled and the ideal or command state that should be obtained. Thus, a factory manager may have predicted output that can be obtained over the next few hours (given workers and equipment available) and a target output that is requested by external demands (i.e., the factory’s client). When systems cannot change their state or productive output easily, we say they are sluggish, or have “high inertia.” In these circumstances of sluggish systems, longer range planning becomes extremely important to guarantee that future production matches future demands. This is because sudden changes in demand cannot be met by rapid changes in system output. Examples of such sluggish systems—in need of planning—are the factory whose equipment takes time to be brought online, the airspace in which aircraft cannot be instantly moved to new locations, or any physical system with high inertia, like a supertanker or a train. In time-critical operations effective planning depends vitally upon anticipating events in the world that might derail the plan implementation. Unfortunately people are not very good at envisioning such events [351], nor the time required to address them. Hence the planning bias, discussed earlier in the chapter, is prevalent. You will recognize the importance to planning of two concepts discussed earlier in this chapter. First, level 3 situation awareness is another way of expressing an accurate estimate of future state and future demands. Second, skilled operators often employ a mental model of the dynamic system to be run through a mental simulation in order to infer the future state from the current state [375]. Mental simulation imposes heavy demands on cognitive resources. If these resources have been depleted or are diverted to other tasks, then prediction and planning may be poor, or not done at all, leaving the operator unprepared for the future. 7.7.1 Principles for Improving Planning and Scheduling Human limits in the area of planning and scheduling are often addressed with automation. Operations research offers many approaches to design the best plan given certain assumptions. Unfortunately, reality often violates these assumptions and people must intervene. 1. Create contingency plans and plan to re-plan. In general, people tend to avoid complex planning schedules over long time horizons [468], a decision driven both by a desire to conserve the resources imposed by high working memory load and by the fact that in an uncertain world accurate planning is impossible, and plans may need to be revised or abandoned altogether as the world evolves in a way that is different from what was predicted. Re-planning is essential. Here, unfortunately, people sometimes fail to do so, creating what is known as a plan continuation error [469, 470], a form of behavior that has much in common with cognitive tunneling, the confirmation bias and the sunk cost bias. Contingency plans and planning to re-plan can avoid these tendencies. 2. Create predictive displays. As with problem solving and troubleshooting, a variety of automation tools are proposed to reduce these cognitive demands in planning [471]. Most effective are predictive displays that offer visual representations of the likely future, reducing the need for working memory [472]. We discuss these in the next chapter. Also potentially useful are computer-based planning aids that can either recommend plans [473] or allow fast-time simulation of the consequence of such plans to allow the operator to try them out and choose the successful one [474]. Air traffic controllers can benefit from such a planning aid known as the User Request Evaluation Tool (URET) to try out different routes to avoid aircraft conflicts [475].